Conformational Sampling of Maltose-transporter Components in Cartesian Collective Variables is Governed by the Low-frequency Normal Modes

Free Energy Surface and Molecular Mechanism of Slow Structural Transitions in Lipid Bilayers

Lipid membrane remodeling, crucial for many cellular processes, is governed by the coupling of membrane structure and shape fluctuations. Given the importance of the ∼ nm length scale, details of the transition intermediates for conformational change are not fully captured by a continuum-mechanical description. Slow dynamics and the lack of knowledge of reaction coordinates (RCs) for biasing methods pose a challenge for all-atom (AA) simulations. Here, we map system dynamics on Langevin dynamics in a normal mode space determined from an elastic network model representation for the lipid-water Hamiltonian. AA molecular dynamics (MD) simulations are used to determine model parameters, and Langevin dynamics predictions for bilayer structural, mechanical, and dynamic properties are validated against MD simulations and experiments. Transferability to describe the dynamics of a larger lipid bilayer and a heterogeneous membrane-protein system is assessed. A set of generic RCs for pore formation in two tensionless bilayers is obtained by coupling Langevin dynamics to the underlying energy landscape for membrane deformations. Structure evolution is carried out by AA MD, wherein the generic RCs are used in a path metadynamics or an umbrella sampling simulation to determine the thermodynamics of pore formation and its molecular determinants, such as the role of distinct bilayer motions, lipid solvation, and lipid packing.

Computation of the Protein Conformational Transition Pathway on Ligand Binding by Linear Response-Driven Molecular Dynamics

While extremely important for relating the protein structure to its biological function, determination of the protein conformational transition pathway upon ligand binding is made difficult due to the transient nature of intermediates, a large and rugged conformational space, and coupling between protein dynamics and ligand-protein interactions. Existing methods that rely on prior knowledge of the bound (holo) state structure are restrictive. A second concern relates to the correspondence of intermediates obtained to the metastable states on the apo → holo transition pathway. Here, we have taken the protein apo structure and ligand-binding site as only inputs and combined an elastic network model (ENM) representation of the protein Hamiltonian with linear response theory (LRT) for protein-ligand interactions to identify the set of slow normal modes of protein vibrations that have a high overlap with the direction of the protein conformational change. The structural displacement along the chosen direction was performed using excited normal modes molecular dynamics (MDeNM) simulations rather than by the direct use of LRT. Herein, the MDeNM excitation velocity was optimized on-the-fly on the basis of its coupling to protein dynamics and ligand-protein interactions. Thus, a determined set of structures was validated against crystallographic and simulation data on four protein-ligand systems, namely, adenylate kinase-di(adenosine-5')pentaphosphate, ribose binding protein-β-d-ribopyranose, DNA β-glucosyltransferase-uridine-5'-diphosphate, and G-protein α subunit-guanosine-5'-triphosphate, which present important differences in protein conformational heterogeneity, ligand binding mechanism, viz. induced-fit or conformational selection, extent, and nonlinearity in protein conformational changes upon ligand binding, and presence of allosteric effects. The obtained set of intermediates was used as an input to path metadynamics simulations to obtain the free energy profile for the apo → holo transition.

Mechanical couplings of protein backbone and side chains exhibit scale-free network properties and specific hotspots for function

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Statistical learning from protein dynamics unravels rigidities in interaction network.

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Backbone and side-chain mechanical couplings exhibit scale-free network properties.

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Graphical depiction of network rigidities captures sequence co-evolution patterns.

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Functional sites at secondary structure peripheries are mechanical hotspots.

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Our rigidity scores are compelling metrics for residue biological significance.

A backbone-side-chain elastic network model (bsENM) is devised in this contribution to decipher the network of molecular interactions during protein dynamics. The chemical details in 5 μs all-atom molecular dynamics (MD) simulation are mapped onto the bsENM spring constants by self-consistent iterations. The elastic parameters obtained by this structure-mechanics statistical learning are then used to construct inter-residue rigidity graphs for the chemical components in protein amino acids. A key discovery is that the mechanical coupling strengths of both backbone and side chains exhibit heavy-tailed distributions and scale-free network properties. In both rat trypsin and PDZ3 proteins, the statistically prominent modes of rigidity graphs uncover the sequence-specific coupling patterns and mechanical hotspots. Based on the contributions to graphical modes, our residue rigidity scores in backbone and side chains are found to be very useful metrics for the biological significance. Most functional sites have high residue rigidity scores in side chains while the biologically important glycines are generally next to mechanical hotspots. Furthermore, prominent modes in the rigidity graphs involving side chains oftentimes coincide with the co-evolution patterns due to evolutionary restraints. The bsENM specifically devised to resolve the protein chemical character thus provides useful means for extracting functional information from all-atom MD.

Increasing the Sampling Efficiency of Protein Conformational Change by Combining a Modified Replica Exchange Molecular Dynamics and Normal Mode Analysis

Understanding conformational change at an atomic level is significant when determining a protein functional mechanism. Replica exchange molecular dynamics (REMD) is a widely used enhanced sampling method to explore protein conformational space. However, REMD with an explicit solvent model requires huge computational resources, immensely limiting its application. In this study, a variation of parallel tempering metadynamics (PTMetaD) with the omission of solvent-solvent interactions in exchange attempts and the use of low-frequency modes calculated by normal-mode analysis (NMA) as collective variables (CVs), namely ossPTMetaD, is proposed with the aim to accelerate MD simulations simultaneously in temperature and geometrical spaces. For testing the performance of ossPTMetaD, five protein systems with diverse biological functions and motion patterns were selected, including large-scale domain motion (AdK), flap movement (HIV-1 protease and BACE1), and DFG-motif flip in kinases (p38α and c-Abl). The simulation results showed that ossPTMetaD requires much fewer numbers of replicas than temperature REMD (T-REMD) with a reduction of ∼70% to achieve a similar exchange ratio. Although it does not obey the detailed balance condition, ossPTMetaD provides consistent results with T-REMD and experimental data. The high accessibility of the large conformational change of protein systems by ossPTMetaD, especially in simulating the very challenging DFG-motif flip of protein kinases, demonstrated its high efficiency and robustness in the characterization of the large-scale protein conformational change pathway and associated free energy profile.

Diffusion network of CO in FeFe-Hydrogenase

FeFe-hydrogenase is an efficient enzyme to produce H₂ under optimal conditions. However, the activity of this enzyme is highly sensitive to the presence of inhibitory gases CO and O₂ that cause irreversible damage to the active site. Therefore, a detailed knowledge of the diffusion pathways of these inhibitory gases is necessary to develop strategies for designing novel enzymes that are tolerant to these gases. In this work, we studied the diffusion pathways of CO in the CpI FeFe-hydrogenase from Clostridium pasteurianum. Specifically, we used several enhanced sampling and free-energy simulation methods to reconstruct a three-dimensional free-energy surface for CO diffusion which revealed 45 free-energy minima forming an interconnected network of pathways. We discovered multiple pathways of minimal free-energy as diffusion portals for CO and found that previously suggested hydrophobic pathways are not thermodynamically favorable for CO diffusion. We also observed that the global minimum in the free-energy surface is located in the vicinity of the active-site metal cluster, the H-cluster, which suggests a high-affinity for CO near the active site. Among 19 potential residues that we propose as candidates for future mutagenesis studies, 11 residues are shared with residues that have been previously proposed to increase the tolerance of this enzyme for O₂. We hypothesize that these shared candidate residues are potentially useful for designing new variants of this enzyme that are tolerant to both inhibitory gases.

Exploring Configuration Space and Path Space of Biomolecules Using Enhanced Sampling Techniques-Searching for Mechanism and Kinetics of Biomolecular Functions

To understand functions of biomolecules such as proteins, not only structures but their conformational change and kinetics need to be characterized, but its atomistic details are hard to obtain both experimentally and computationally. Here, we review our recent computational studies using novel enhanced sampling techniques for conformational sampling of biomolecules and calculations of their kinetics. For efficiently characterizing the free energy landscape of a biomolecule, we introduce the multiscale enhanced sampling method, which uses a combined system of atomistic and coarse-grained models. Based on the idea of Hamiltonian replica exchange, we can recover the statistical properties of the atomistic model without any biases. We next introduce the string method as a path search method to calculate the minimum free energy pathways along a multidimensional curve in high dimensional space. Finally we introduce novel methods to calculate kinetics of biomolecules based on the ideas of path sampling: one is the Onsager⁻Machlup action method, and the other is the weighted ensemble method. Some applications of the above methods to biomolecular systems are also discussed and illustrated.

Building Graphs To Describe Dynamics, Kinetics, and Energetics in the d-ALa:d-Lac Ligase VanA

The d-Ala:d-Lac ligase, VanA, plays a critical role in the resistance of vancomycin. Indeed, it is involved in the synthesis of a peptidoglycan precursor, to which vancomycin cannot bind. The reaction catalyzed by VanA requires the opening of the so-called “ω-loop”, so that the substrates can enter the active site. Here, the conformational landscape of VanA is explored by an enhanced sampling approach: the temperature-accelerated molecular dynamics (TAMD). Analysis of the molecular dynamics (MD) and TAMD trajectories recorded on VanA permits a graphical description of the structural and kinetics aspects of the conformational space of VanA, where the internal mobility and various opening modes of the ω-loop play a major role. The other important feature is the correlation of the ω-loop motion with the movements of the opposite domain, defined as containing the residues A149–Q208. Conformational and kinetic clusters have been determined and a path describing the ω-loop opening was extracted from these clusters. The determination of this opening path, as well as the relative importance of hydrogen bonds along the path, permit one to propose some key residue interactions for the kinetics of the ω-loop opening.

ClustENM: ENM-Based Sampling of Essential Conformational Space at Full Atomic Resolution

Accurate sampling of conformational space and, in particular, the transitions between functional substates has been a challenge in molecular dynamic (MD) simulations of large biomolecular systems. We developed an Elastic Network Model (ENM)-based computational method, ClustENM, for sampling large conformational changes of biomolecules with various sizes and oligomerization states. ClustENM is an iterative method that combines ENM with energy minimization and clustering steps. It is an unbiased technique, which requires only an initial structure as input, and no information about the target conformation. To test the performance of ClustENM, we applied it to six biomolecular systems: adenylate kinase (AK), calmodulin, p38 MAP kinase, HIV-1 reverse transcriptase (RT), triosephosphate isomerase (TIM), and the 70S ribosomal complex. The generated ensembles of conformers determined at atomic resolution show good agreement with experimental data (979 structures resolved by X-ray and/or NMR) and encompass the subspaces covered in independent MD simulations for TIM, p38, and RT. ClustENM emerges as a computationally efficient tool for characterizing the conformational space of large systems at atomic detail, in addition to generating a representative ensemble of conformers that can be advantageously used in simulating substrate/ligand-binding events.

Ligand Docking to Intermediate and Close-To-Bound Conformers Generated by an Elastic Network Model Based Algorithm for Highly Flexible Proteins

Incorporating receptor flexibility in small ligand-protein docking still poses a challenge for proteins undergoing large conformational changes. In the absence of bound structures, sampling conformers that are accessible by apo state may facilitate docking and drug design studies. For this aim, we developed an unbiased conformational search algorithm, by integrating global modes from elastic network model, clustering and energy minimization with implicit solvation. Our dataset consists of five diverse proteins with apo to complex RMSDs 4.7-15 Å. Applying this iterative algorithm on apo structures, conformers close to the bound-state (RMSD 1.4-3.8 Å), as well as the intermediate states were generated. Dockings to a sequence of conformers consisting of a closed structure and its "parents" up to the apo were performed to compare binding poses on different states of the receptor. For two periplasmic binding proteins and biotin carboxylase that exhibit hinge-type closure of two dynamics domains, the best pose was obtained for the conformer closest to the bound structure (ligand RMSDs 1.5-2 Å). In contrast, the best pose for adenylate kinase corresponded to an intermediate state with partially closed LID domain and open NMP domain, in line with recent studies (ligand RMSD 2.9 Å). The docking of a helical peptide to calmodulin was the most challenging case due to the complexity of its 15 Å transition, for which a two-stage procedure was necessary. The technique was first applied on the extended calmodulin to generate intermediate conformers; then peptide docking and a second generation stage on the complex were performed, which in turn yielded a final peptide RMSD of 2.9 Å. Our algorithm is effective in producing conformational states based on the apo state. This study underlines the importance of such intermediate states for ligand docking to proteins undergoing large transitions.

Dimensionality of Collective Variables for Describing Conformational Changes of a Multi-Domain Protein

Collective variables (CVs) are often used in molecular dynamics simulations based on enhanced sampling algorithms to investigate large conformational changes of a protein. The choice of CVs in these simulations is essential because it affects simulation results and impacts the free-energy profile, the minimum free-energy pathway (MFEP), and the transition-state structure. Here we examine how many CVs are required to capture the correct transition-state structure during the open-to-close motion of adenylate kinase using a coarse-grained model in the mean forces string method to search the MFEP. Various numbers of large amplitude principal components are tested as CVs in the simulations. The incorporation of local coordinates into CVs, which is possible in higher dimensional CV spaces, is important for capturing a reliable MFEP. The Bayesian measure proposed by Best and Hummer is sensitive to the choice of CVs, showing sharp peaks when the transition-state structure is captured. We thus evaluate the required number of CVs needed in enhanced sampling simulations for describing protein conformational changes.

Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review

Molecular Dynamics simulations are a powerful approach to study biomolecular conformational changes or protein-ligand, protein-protein, and protein-DNA/RNA interactions. Straightforward applications, however, are often hampered by incomplete sampling, since in a typical simulated trajectory the system will spend most of its time trapped by high energy barriers in restricted regions of the configuration space. Over the years, several techniques have been designed to overcome this problem and enhance space sampling. Here, we review a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study. In particular, we illustrate the Temperature Accelerated Molecular Dynamics (TAMD), Logarithmic Mean Force Dynamics (LogMFD), and Multiscale Enhanced Sampling (MSES) algorithms. We also discuss combinations with techniques for searching reaction paths. We show the advantages presented by this approach and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.

Conformational Motions and Functionally Key Residues for Vitamin B12 Transporter BtuCD-BtuF Revealed by Elastic Network Model with a Function-Related Internal Coordinate

BtuCD-BtuF from Escherichia coli is a binding protein-dependent adenosine triphosphate (ATP)-binding cassette (ABC) transporter system that uses the energy of ATP hydrolysis to transmit vitamin B12 across cellular membranes. Experimental studies have showed that during the transport cycle, the transporter undergoes conformational transitions between the "inward-facing" and "outward-facing" states, which results in the open-closed motions of the cytoplasmic gate of the transport channel. The opening-closing of the channel gate play critical roles for the function of the transporter, which enables the substrate vitamin B12 to be translocated into the cell. In the present work, the extent of opening of the cytoplasmic gate was chosen as a function-related internal coordinate. Then the mean-square fluctuation of the internal coordinate, as well as the cross-correlation between the displacement of the internal coordinate and the movement of each residue in the protein, were calculated based on the normal mode analysis of the elastic network model to analyze the function-related motions encoded in the structure of the system. In addition, the key residues important for the functional motions of the transporter were predicted by using a perturbation method. In order to facilitate the calculations, the internal coordinate was introduced as one of the axes of the coordinate space and the conventional Cartesian coordinate space was transformed into the internal/Cartesian space with linear approximation. All the calculations were carried out in this internal/Cartesian space. Our method can successfully identify the functional motions and key residues for the transporter BtuCD-BtuF, which are well consistent with the experimental observations.

Oncogenic mutations weaken the interactions that stabilize the p110α-p85α heterodimer in phosphatidylinositol 3-kinase α

Phosphatidylinositol 3-kinase (PI3K) α is a heterodimeric lipid kinase that catalyzes the conversion of phosphoinositol-4,5-bisphosphate to phosphoinositol-3,4,5-trisphosphate. The PI3Kα signaling pathway plays an important role in cell growth, proliferation, and survival. This pathway is activated in numerous cancers, where the PI3KCA gene, which encodes for the p110α PI3Kα subunit, is mutated. Its mutation often results in gain of enzymatic activity; however, the mechanism of activation by oncogenic mutations remains unknown. Here, using computational methods, we show that oncogenic mutations that are far from the catalytic site and increase the enzymatic affinity destabilize the p110α-p85α dimer. By affecting the dynamics of the protein, these mutations favor the conformations that reduce the autoinhibitory effect of the p85α nSH2 domain. For example, we determined that, in all of the mutants, the nSH2 domain shows increased positional heterogeneity as compared with the wild-type, as demonstrated by changes in the fluctuation profiles computed by normal mode analysis of coarse-grained elastic network models. Analysis of the interdomain interactions of the wild-type and mutants at the p110α-p85α interface obtained with molecular dynamics simulations suggest that all of the tumor-associated mutations effectively weaken the interactions between p110α and p85α by disrupting key stabilizing interactions. These findings have important implications for understanding how oncogenic mutations change the conformational multiplicity of PI3Kα and lead to increased enzymatic activity. This mechanism may apply to other enzymes and/or macromolecular complexes that play a key role in cell signaling.

Analysis of the Free Energy Landscapes for the Opening-Closing Dynamics of the Maltose Transporter ATPase MalK2 Using Enhanced-Sampling Molecular Dynamics Simulation

Protein dynamics are considered significant for many physiological processes, such as metabolism, biomolecular recognition, and the regulation of several vital cellular processes. Due to their flexibility, proteins may stay in different substates with or without the existence of the cognate substrates. To describe these phenomena, two models have been proposed: the "induced fit" and the "conformational selection" mechanisms. In this study, we used MalK2, the subunits that mainly include the nucleotide-binding domains (NBDs) of the maltose transporter from Escherichia coli, as a target to understand the NBD dimerization mechanism. Accelerated and conventional molecular dynamics have been performed. The results revealed that Mg-ATP binding to MalK2 led to a significant change in the free energy profile and thus stabilized the closed conformation. On the contrary, when Mg-ATP was removed, the open conformation would be favored. The fact that ligand binding induces a drastic free energy change leads to a significant inference: MalK2 dimerization would occur through the induced-fit mechanism rather than the conformational selection mechanism. This study sheds new light on the NBD dimerization mechanism and would be of wide applicability to other ABC transporters.

Temperature Accelerated Molecular Dynamics with Soft-Ratcheting Criterion Orients Enhanced Sampling by Low-Resolution Information

Many proteins exhibit an equilibrium between multiple conformations, some of them being characterized only by low-resolution information. Visiting all conformations is a demanding task for computational techniques performing enhanced but unfocused exploration of collective variable (CV) space. Otherwise, pulling a structure toward a target condition biases the exploration in a way difficult to assess. To address this problem, we introduce here the soft-ratcheting temperature-accelerated molecular dynamics (sr-TAMD), where the exploration of CV space by TAMD is coupled to a soft-ratcheting algorithm that filters the evolving CV values according to a predefined criterion. Any low resolution or even qualitative information can be used to orient the exploration. We validate this technique by exploring the conformational space of the inactive state of the catalytic domain of the adenyl cyclase AC from Bordetella pertussis. The domain AC gets activated by association with calmodulin (CaM), and the available crystal structure shows that in the complex the protein has an elongated shape. High-resolution data are not available for the inactive, CaM-free protein state, but hydrodynamic measurements have shown that the inactive AC displays a more globular conformation. Here, using as CVs several geometric centers, we use sr-TAMD to enhance CV space sampling while filtering for CV values that correspond to centers moving close to each other, and we thus rapidly visit regions of conformational space that correspond to globular structures. The set of conformations sampled using sr-TAMD provides the most extensive description of the inactive state of AC up to now, consistent with available experimental information.

Rigidity, secondary structure, and the universality of the boson peak in proteins

Complementary neutron- and light-scattering results on nine proteins and amino acids reveal the role of rigidity and secondary structure in determining the time- and lengthscales of low-frequency collective vibrational dynamics in proteins. These dynamics manifest in a spectral feature, known as the boson peak (BP), which is common to all disordered materials. We demonstrate that BP position scales systematically with structural motifs, reflecting local rigidity: disordered proteins appear softer than α-helical proteins; which are softer than β-sheet proteins. Our analysis also reveals a universal spectral shape of the BP in proteins and amino acid mixtures; superimposable on the shape observed in typical glasses. Uniformity in the underlying physical mechanism, independent of the specific chemical composition, connects the BP vibrations to nanometer-scale heterogeneities, providing an experimental benchmark for coarse-grained simulations, structure/rigidity relationships, and engineering of proteins for novel applications.

Theoretical and computational studies of peptides and receptors of the insulin family

Synergistic interactions among peptides and receptors of the insulin family are required for glucose homeostasis, normal cellular growth and development, proliferation, differentiation and other metabolic processes. The peptides of the insulin family are disulfide-linked single or dual-chain proteins, while receptors are ligand-activated transmembrane glycoproteins of the receptor tyrosine kinase (RTK) superfamily. Binding of ligands to the extracellular domains of receptors is known to initiate signaling via activation of intracellular kinase domains. While the structure of insulin has been known since 1969, recent decades have seen remarkable progress on the structural biology of apo and liganded receptor fragments. Here, we review how this useful structural information (on ligands and receptors) has enabled large-scale atomically-resolved simulations to elucidate the conformational dynamics of these biomolecules. Particularly, applications of molecular dynamics (MD) and Monte Carlo (MC) simulation methods are discussed in various contexts, including studies of isolated ligands, apo-receptors, ligand/receptor complexes and intracellular kinase domains. The review concludes with a brief overview and future outlook for modeling and computational studies in this family of proteins.

Temperature-accelerated molecular dynamics gives insights into globular conformations sampled in the free state of the AC catalytic domain

The catalytic domain of the adenyl cyclase (AC) toxin from Bordetella pertussis is activated by interaction with calmodulin (CaM), resulting in cAMP overproduction in the infected cell. In the X-ray crystallographic structure of the complex between AC and the C terminal lobe of CaM, the toxin displays a markedly elongated shape. As for the structure of the isolated protein, experimental results support the hypothesis that more globular conformations are sampled, but information at atomic resolution is still lacking. Here, we use temperature-accelerated molecular dynamics (TAMD) simulations to generate putative all-atom models of globular conformations sampled by CaM-free AC. As collective variables, we use centers of mass coordinates of groups of residues selected from the analysis of standard molecular dynamics (MD) simulations. Results show that TAMD allows extended conformational sampling and generates AC conformations that are more globular than in the complexed state. These structures are then refined via energy minimization and further unrestrained MD simulations to optimize inter-domain packing interactions, thus resulting in the identification of a set of hydrogen bonds present in the globular conformations.

Conformational changes in acetylcholine binding protein investigated by temperature accelerated molecular dynamics

Despite the large number of studies available on nicotinic acetylcholine receptors, a complete account of the mechanistic aspects of their gating transition in response to ligand binding still remains elusive. As a first step toward dissecting the transition mechanism by accelerated sampling techniques, we study the ligand-induced conformational changes of the acetylcholine binding protein (AChBP), a widely accepted model for the full receptor extracellular domain. Using unbiased Molecular Dynamics (MD) and Temperature Accelerated Molecular Dynamics (TAMD) simulations we investigate the AChBP transition between the apo and the agonist-bound state. In long standard MD simulations, both conformations of the native protein are stable, while the agonist-bound structure evolves toward the apo one if the orientation of few key sidechains in the orthosteric cavity is modified. Conversely, TAMD simulations initiated from the native conformations are able to produce the spontaneous transition. With respect to the modified conformations, TAMD accelerates the transition by at least a factor 10. The analysis of some specific residue-residue interactions points out that the transition mechanism is based on the disruption/formation of few key hydrogen bonds. Finally, while early events of ligand dissociation are observed already in standard MD, TAMD accelerates the ligand detachment and, at the highest TAMD effective temperature, it is able to produce a complete dissociation path in one AChBP subunit.

Conformational dynamics of a regulator of G-protein signaling protein reveals a mechanism of allosteric inhibition by a small molecule

Regulators of G protein signaling (RGS) proteins are key players in regulating signaling via G protein-coupled receptors. RGS proteins directly bind to the Gα-subunits of activated heterotrimeric G-proteins, and accelerate the rate of GTP hydrolysis, thereby rapidly deactivating G-proteins. Using atomistic simulations and NMR spectroscopy, we have studied in molecular detail the mechanism of action of CCG-50014, a potent small molecule inhibitor of RGS4 that covalently binds to cysteine residues on RGS4. We apply temperature-accelerated molecular dynamics (TAMD) to carry out enhanced conformational sampling of apo RGS4 structures, and consistently find that the α5-α6 helix pair of RGS4 can spontaneously span open-like conformations, allowing binding of CCG-50014 to the buried side-chain of Cys95. Both NMR experiments and MD simulations reveal chemical shift perturbations in residues in the vicinity of inhibitor binding site as well as in the RGS4-Gα binding interface. Consistent with a loss of G-protein binding, GAP activity, and allosteric mechanism of action of CCG-50014, our simulations of the RGS4-Gα complex in the presence of inhibitor suggest a relatively unstable protein-protein interaction. These results have potential implications for understanding how the conformational dynamics among RGS proteins may play a key role in the sensitivity of inhibitors.

Crowding induced collective hydration of biological macromolecules over extended distances

Ultrafast two-dimensional infrared (2D-IR) spectroscopy reveals picosecond protein and hydration dynamics of crowded hen egg white lysozyme (HEWL) labeled with a metal-carbonyl vibrational probe covalently attached to a solvent accessible His residue. HEWL is systematically crowded alternatively with polyethylene glycol (PEG) or excess lysozyme in order to distinguish the chemically inert polymer from the complex electrostatic profile of the protein crowder. The results are threefold: (1) A sharp dynamical jamming-like transition is observed in the picosecond protein and hydration dynamics that is attributed to an independent-to-collective hydration transition induced by macromolecular crowding that slows the hydration dynamics up to an order of magnitude relative to bulk water. (2) The interprotein distance at which the transition occurs suggests collective hydration of proteins over distances of 30-40 Å. (3) Comparing the crowding effects of PEG400 to our previously reported experiments using glycerol exposes fundamental differences between small and macromolecular crowding agents.

Enhanced sampling and overfitting analyses in structural refinement of nucleic acids into electron microscopy maps

Flexible fitting computational algorithms are often useful to interpret low-resolution maps of many macromolecular complexes generated by electron microscopy (EM) imaging. One such atomistic simulation technique is molecular dynamics flexible fitting (MDFF), which has been widely applied to generate structural models of large ribonucleoprotein assemblies such as the ribosome. We have previously shown that MDFF simulations of globular proteins are sensitive to the resolution of the target EM map and the strength of restraints used to preserve the secondary structure elements during fitting (Vashisth, H.; et al. Structure 2012, 20, 1453-1462). In this work, we aim to systematically examine the quality of structural models of various nucleic acids obtained via MDFF by varying the map resolution and the strength of structural restraints. We also demonstrate how an enhanced conformational sampling technique for proteins, temperature-accelerated molecular dynamics (TAMD), can be combined with MDFF for the structural refinement of nucleic acids in EM maps. Finally, we also demonstrate application of TAMD-assisted MDFF (TAMDFF) on a RNA/protein complex and suggest that TAMDFF is a viable strategy for enhanced conformational fitting in target maps of ribonucleoprotein complexes.